Eagle-449: A volumetric, whole-brain compilation of brain atlases for vestibular functional MRI research

Human vestibular processing involves distributed networks of cortical and subcortical regions which perform sensory and multimodal integrative functions. These functional hubs are also interconnected with areas subserving cognitive, affective, and body-representative domains. Analysis of these diverse components of the vestibular and vestibular-associated networks, and synthesis of their holistic functioning, is therefore vital to our understanding of the genesis of vestibular dysfunctions and aid treatment development. Novel neuroimaging methodologies, including functional and structural connectivity analyses, have provided important contributions in this area, but often require the use of atlases which are comprised of well-defined a priori regions of interest. Investigating vestibular dysfunction requires a more detailed atlas that encompasses cortical, subcortical, cerebellar, and brainstem regions. The present paper represents an effort to establish a compilation of existing, peer-reviewed brain atlases which collectively afford comprehensive coverage of these regions while explicitly focusing on vestibular substrates. It is expected that this compilation will be iteratively improved with additional contributions from researchers in the field.


Methods
Generation of the vestibular atlas. Six parcellations were leveraged for this compilation, including the Eickhoff Anatomy atlas, which is a primary component of the JuBrain/SPM Anatomy Toolbox (https://github. com/inm7/jubrain-anatomy-toolbox) [50][51][52] ; the SUIT anatomical cerebellar parcellation by Diedrichsen et al. (https://github.com/DiedrichsenLab/cerebellar_atlases/tree/master/Diedrichsen_2009) 53 ; anatomical parcellations of the thalamus 54 and hypothalamus 55 by Najdenovska et al. 56 and Neudorfer et al. 57 respectively; and divisions of the brainstem and diencephalon provided as part of the Brainstem Navigator template [58][59][60][61][62][63][64] . All cortical areas not included in the Eickhoff parcellation were obtained from the Brainnetome atlas (https://atlas.brainnetome.org) by Fan et al. [65][66][67][68][69] . All atlases were resampled to MNI152 stereotactic space, if necessary, registered to the 1 mm isometric MNI152 T1 template (version 2009c) using 3-dof linear registration, inspected and corrected for overlapping voxels, and masked against the MNI152 white matter and cerebrospinal fluid templates. "Orphan" voxels, defined as very small voxel clusters which were not contiguous with a larger cluster in-plane or within adjacent slices, were then removed using the AFNI program 3dmerge 70 , which performed voxel clustering using a maximum inter-voxel connection radius of 1.7 mm. Finally, "liminal" voxels, defined as contiguous but thin edges of 1-4 voxel thickness, and which were usually the result of remnant ROI edges, often in occipital cortex, following subtraction of other atlases from the Brainnetome parcellation, were manually removed by editing in AFNI (Fig. 1).
Additional preprocessing details for each parcellation are provided below. For a comprehensive list of all ROIs obtained from each atlas, as well as atlas labels, ROI values, and ROI size, refer to Supplementary Tables -Atlas Labels. All preprocessed parcellations, ROI label files (also known as lookup tables or LUTs), and preprocessing Brainnetome structural-functional cortical parcellation (Atlas A2). The JuBrain parcellation does not comprise the entire cerebral cortex, and some areas commonly associated with vestibular processing, including hMST and visual cingulate (caudal Brodmann area 23), are not well-defined. Consequently, all cortical ROIs not defined in Atlas A1 were generated from the Brainnetome atlas, which is premised on the functional and structural connectivity of cortical regions, as Atlas A2. To avoid overlaps with other parcellations, a binary mask comprised of atlases A1, A3 (cerebellar), B1 (thalamic), B2 (brainstem), and B3 (diencephalon) was subtracted from the Brainnetome parcellation. As a result of this subtraction, some ROIs conventionally included in the Brainnetome parcellation, including occipitopolar cortex (OPC), medioventral (cLinG) and lateral occipital cortex (iOccG), L lateral amygdala (lAmygL), and R entorhinal area 28/34 (A28/34), contain zero voxels in the final Atlas A2. However, these regions are indexed in the LUTs for comprehensiveness, for a total 229 Atlas A2 ROIs.
The Brainnetome parcellation does not contain cerebellar ROIs, but does define several ROIs from subcortical structures, including cingulate, caudate, putamen, globus pallidus, and nucleus accumbens, and these structures are also included in Atlas A2. Additionally, some larger cortical areas, such as superior parietal area hIPS3 and postcentral area 2, are more restrictively defined in the JuBrain/A1 atlas, and portions of these areas which are contiguous with, but do not overlap with, A1 areas are also included in Atlas A2. Finally, Atlas A2 contains liminal remnants of other cortical regions which were not defined as part of other atlases, but were too large and Cortical areas not included in atlas A1 were incorporated from the Fan Brainnetome atlas as atlas A2. In all cases, source ROIs were aligned to the 1 mm isometric MNI152 T1 template and adjusted for overlaps, as detailed in the text; additionally, some hypothalamic ROIs were merged and downsampled from the source 0.5 mm isometric to final 1 mm isometric grid. All T1-registered source ROIs were masked against cerebrospinal fluid and white matter templates, and isolated voxel clusters were edited manually and via clustering (Ensure non-overlap panel). Finally, lookup tables were generated for each of the final seven atlases for import into the CONN Toolbox (Build atlas panel).
www.nature.com/scientificdata www.nature.com/scientificdata/ contiguous to be considered "orphan" voxel clusters. These remnants are typically found in the occipital lobe in the vicinity of the parieto-occipital sulcus. cerebellar parcellation. Diedrichsen-SUIT anatomical parcellation (Atlas A3). The SUIT cerebellar atlas is premised on anatomical delineations of cerebellar structures and is provided as part of the SUIT Toolbox. It was incorporated into this compilation, without modification, as Atlas A3, and is comprised of 34 ROIs. ROIs included in the SUIT parcellation were subtracted from other atlases, as noted elsewhere in this section.
Subcortical and brainstem structures. Najdenovska anatomical thalamus parcellation (Atlas B1). Many atlases include a delineation of the thalamus which is based on the functional connectivity analyses by Behrens et al. 91,92 . Our present atlas compilation, however, is primarily based on anatomical delineation of cerebral structures, and, for consistency, we opted to include the thalamic parcellation by Najdenovska et al. 56 as Atlas B1, comprised of 14 ROIs. Brainstem and diencephalon ROIs (atlases B2 and B3) overlapped with the edges of some of these thalamic areas by approximately 1-3 voxels, and were subtracted from Atlas B1 accordingly. A mask comprised of ROIs from Atlas B1 was also subtracted from atlases A1 and A2, as previously noted, as well as from Atlas B4 (hypothalamus). Lateral and medial geniculate nuclei (LGN, MGN) were included with diencephalic regions (Atlas B3).
Brainstem Navigator (brainstem and diencephalon: Atlases B2 and B3). Brainstem and diencephalon ROIs were incorporated into this atlas compilation as Atlases B2 and B3, respectively. Some minor overlaps of 1-2 voxels were noted among these ROIs; accordingly, each pair of ROIs was assessed for voxel overlap, and overlapping voxels were retained from the smaller, and subtracted from the larger, of the pair. A mask of the Atlas B2 and B3 ROIs was created following this procedure and subtracted from atlases A1 and B1, as previously noted, as well as from Atlas B4 (hypothalamus). The final B2 atlas was comprised of 66 ROIs, and the B3 atlas of 6 ROIs, including L and R LGN and MGN and L and R subthalamic nuclei. Notably, the vestibular nuclei complex, an important component of the vestibular system, is included in Atlas B2 (Table 1).

Neudorfer anatomical hypothalamus parcellation (Atlas B4). The detailed hypothalamic parcellation by
Neudorfer and colleagues 57 is originally defined in 0.5 mm isometric space and required additional processing for inclusion in the 1 mm compilation. As part of this process, larger ROIs, such as the L and R mamillary bodies, www.nature.com/scientificdata www.nature.com/scientificdata/ bed nuclei of the stria terminali, and L and R nucleus basalis were retained; however, the final 1 mm resolution, relative to the size of several other nuclei of interest, including the medial preoptic, paraventricular, periventricular, dorsal periventricular, ventromedial, dorsomedial, supraoptic, suprachiasmatic, tuberomammillary, and arcuate nuclei, as well as the lateral, anterior, and posterior hypothalamus, necessitated their merger into L and R "hypothalamus, not otherwise specified (NOS)" ROIs. Downsampling to the 1 mm isometric grid was performed with the AFNI program 3dfractionize; various 3dfractionize clipping levels (percent voxel occupation) from 0.1 (10%) to 0.8 (80%) were assessed, and a clipping level of 40% ultimately selected, as this yielded ROI borders which most closely matched those in the original, 0.5 mm isometric grid. Minor overlaps between the Neudorfer hypothalamus, Brainstem Navigator, and Najdenovska thalamus ROIs were resolved by subtraction of binary masks representing atlases B1, B2, and B3 from the downsampled ROIs. Eight ROIs remained after this subtraction and are included in the compilation as Atlas B4. A partial view of the original Neudorfer et al. and final www.nature.com/scientificdata www.nature.com/scientificdata/ Atlas B4 ROIs, following downsampling and subtraction of brainstem and diencephalon ROIs (Atlas B2 and B3), is provided as Supplementary Figure 2.

Data Records
The Eagle-449 atlas compilation has been made available on NITRC 73 , under an open/attribution license, in the form of Gzipped, NIfTI-format volumetric datasets for atlases a1-a3 and b1-b4; text-format lookup tables (LUTs) for each atlas based on assigned ROI value; a spreadsheet containing ROI values, abbreviations, full labels, ROI group (e.g., somatomotor, orbitofrontal, cerebellum); and suggested ROI labels and ROI ordering for use with the CONN Toolbox 73 . The present version, v449, resides in the EAGLE449 folder on the associated GitHub repository, and it is expected that future iterations of the atlas compilation, which will be based on additional contributions from vestibular neuroimaging researchers, will be placed in separate subfolders in the same repository.

Technical Validation
participants and MRI acquisitions. The present study evaluated rsfMRI data from a total 821 datasets from young, healthy adult subjects (402 male, 419 female) included in the HCP S500 (n = 269), S900 (n = 350), and S1200 (n = 202) public data releases. Additional information on HCP inclusion and exclusion criteria may be found in Van Essen 42 . One rsfMRI acquisition, acquired using a Siemens Skyra 3 T MRI (1200 frames at TR = 720msec, 72 slices, TE = 33.1msec, FA = 52°, 2 mm isometric voxels, 208 × 180 mm FOV) 93 , previously denoised by the HCP using the FIX denoising pipeline and normalized to the standard MNI152 brain template (REST1_LR_hp2000_clean), as well as a preprocessed T1-weighted anatomical image, was obtained for each participant. The FIX pipeline includes application of a highpass filter at 2000 sec, motion regression, and regression of noise components identified via independent components analysis 94 . Only data preprocessed with the most recent HCP preprocessing workflow, version r227, were included. Subject ages ranged from 22 to 36 years (see Table 2). Data preprocessing. Given the denoising and normalization already applied to the subject T1 and resting state data as part of the FIX-denoising process, the current workflow, performed in the CONN Toolbox version 21b, was limited to minimal preprocessing standards and consisted of tissue segmentation to obtain mean white matter and CSF signal, minimal correction or residual subject motion and identification of framewise outliers, ordinary least-squares regression of white matter, CSF, and motion noise sources, and smoothing of residual data using a 4 mm FWHM Gaussian kernel as well as an 8-250 mHz bandpass. Quality assurance results are provided as Supplementary Figure 1 -Quality Control.

Functional connectivity analysis.
To test the atlas compilation, semipartial correlations were computed, using the CONN Toolbox, between the right (R) OP2, R PIC, and all 447 remaining ROIs from the seven component parcellations. The semipartial correlation coefficient, or SPCC, between ROI pairs controls for other ROIs' mediating effects on those pairs, and thus represents an estimate of the "direct" or "effective" connectivity between them [95][96][97] . For this analysis, the Fisher-transformed SPCC, Z(i, j), was computed for each pair of ROIs using the ROI timeseries R i (t) and the matrix β of multivariate regression coefficients: is estimated by ordinary least squares: The matrix Z of all SPCCs was then subjected to a one-sample t-test and a "threshold-free cluster enhancement" (TFCE) score 98 computed for each connection and for groups of neighboring connections  www.nature.com/scientificdata www.nature.com/scientificdata/ (subgraphs or "clusters") from the resulting matrix of t-statistics. Hypothesis testing proceeded by comparing the t-value for each connection with an estimate of a TFCE "extent" parameter at various thresholds and comparing the results with an expected null distribution of TFCE values estimated using 1000 permutations of the original data. This procedure yielded a "peak-level" familywise error rate (FWE)-corrected p-value, representing the likelihood of detecting one or more connections with the observed TFCE value or larger over all connections in Z. "Peak-level" uncorrected and false discovery rate (FDR)-corrected p-values were also estimated for each local extremum in the TFCE score matrix, representing the likelihood of observing its TFCE score, or larger, in at least one other randomly-selected extremum in the TFCE score matrix, or the expected proportion of false discoveries for that extremum's TFCE score or greater 97,99 . For hypothesis testing, the current TFCE results were corrected for multiple comparisons at p(FWE) ≤0.05.
The CONN Toolbox computes TFCE using an exact integration method. Note that the definition of a "cluster" of connections for TFCE is partly dependent on ROI sorting, and this sorting algorithm may be implemented manually or through hierarchical clustering based on anatomical proximity or functional similarity 100 . For the present (exploratory) purposes, ROIs were sorted by anatomical or functional domain, including www.nature.com/scientificdata www.nature.com/scientificdata/ vestibular or extended vestibular based on prior publications 14,15 , or orbitofrontal-prefrontal, frontal, somatomotor, somatosensory, visual, superior or inferior parietal, superior or middle-temporal, medial temporal, insular, and cingulate. FWE, FDR, and uncorrected p-values for connection clusters and individual connections did not differ substantially between this manual sorting and the default CONN hierarchical algorithm; other algorithms may, however, be preferable 101 .
Results. Semipartial correlations, corrected for multiple comparisons using TFCE, are shown for the R OP2 and R PIC seed ROIs in Fig. 3, 4, respectively, and results provided for first-order connections to these ROIs are presented in Table 3. R OP2 connections in this normative cohort included R parietal area PFcm, OP1, OP3, insular areas G, Ig1, and Ig2, PIC, and rostrodorsal area 40 (40rd/area PFt), as well as L OP2. Connections with R PIC included R PFcm, PF, OP1, OP3, OP2, rostroventral area 40 (area PFop), and rostrodorsal area 40/PFt, as well as L OP2. Note that, although TFCEs for the R OP2:R PFcm, R OP2:R 40rd/PFt, R PIC:40rd/PFt, and R PIC-L OP2 parent clusters were statistically significant at p(FWE)≤0.05 and p(FDR)≤0.05, these associations did not survive multiple comparisons correction at the connection level. These results compare favorably with the structural www.nature.com/scientificdata www.nature.com/scientificdata/ findings of Indovina et al. 15 except that no connection between R PIC and L motor area 4a was observed in the current results, but were reported by Indovina et al., and a connection between R OP2 and ipsilateral PFt was observed in the current results, but was not reported by Indovina et al. Additionally, a suprathreshold number of streamlines originating from, or terminating in, R OP2 or R PIC, were observed in the latter study which were not supported, in terms of functional connectivity, here. Neither R OP2 nor R PIC exhibited connectivity with thalamic, brainstem, or cerebellar nuclei. In both cases, however, connectivity was predominantly localized to the right hemisphere, and characterized by homotopic connections with the seed ROIs. All semipartial correlations were positive, indicating in-phase relationships between the seed and target ROIs.
Statistics for all extant connections following TFCE correction are also provided as Supplementary Table 2. Several interesting connections were observed between conventional vestibular regions and areas not typically included in the "core" vestibular network, including R somatosensory area 2 and ipsilateral rostral hippocampus (connection t = +2.3800, p(FDR) = 0.0176, but p(FWE) = 0.3157), R area 7ip and ipsilateral laterobasal amygdala (connection t = +1.8700, but p(FDR) = 0.0623 and p(FWE) = 0.5625), and extensive interconnectivity between cortical vestibular areas 37 dl/hMST and 7ip and visual areas FG2, FG4, lateral-anterior and lateral-posterior area hOc4, and between hOc5, postcentral area 2, and regions of the cerebellum, including L crus, R V, VI, VIIb, and VIIIa. Additionally, several cortical and subcortical vestibular areas, including area PF and the vestibular nucleus complex, were functionally connected with subcortical and brainstem nuclei, such as the subcoeruleus, laterodorsal tegmental nucleus, medial parabrachial nucleus, globus pallidus, and caudal-dorsal cingulate area 24.
Limitations of the validation process. The current version, v449, of the atlas compilation, as well as its technical validation, incurs several caveats. With respect to the compilation itself, it is important to note that the Brainnetome parcellation (Atlas A2) serves as a "catch-all" for cortical areas not included in Atlas A1, and, as previously noted, includes liminal remnants of Atlas A1 ROIs. Consequently, Atlas A2 should not be used independently of Atlas A1, and future versions of the atlas compilation may substitute other anatomically-derived cortical parcellations for, or in addition to, the Brainnetome source. Investigators are also encouraged to consider whether the Brainnetome parcellation comports with their research aims, as some cortical parcellations, including functionally-defined parcellations such as that of Gordon et al. 102   www.nature.com/scientificdata www.nature.com/scientificdata/ including OP2, it appears likely that these areas, as currently defined, are composites of subregions which subserve differential vestibular functions 49 .
"Validation" of the current atlas compilation was conducted by computing semi-partial correlation coefficients between right-hemisphere OP2 and PIC seeds and all other ROIs, and comparing the results to previous peer-reviewed findings concerning the connectivity of these regions 14,15 . While these qualitative comparisons were favorable in that they replicated prior results, it should be noted that there are numerous ways, in addition to semi-partial correlation, to assess RSFC. Analyses which leveraged "classical" Pearson correlations failed to resolve network structures, such as connections between vestibular nuclei and other areas, which would be expected based on prior anatomical and structural findings in humans and lower primates, and the technical validation process therefore leveraged semi-partial correlations in order to control for the influence of all other connections with the seed and target ROIs. Due to the nature of semi-partial correlation, however, removing one or more of these regions may effect a new network topology. Finally, the topologies resolved in this validation process are likely incomplete, due not only to inherent issues of multiple comparisons (which were addressed to some degree by the use of TFCE), but potentially due to suppressed effect sizes in the connectivity of the subcortical regions of HCP datasets due to MRI acquisition parameters, which have been noted as problematic by Risk and colleagues 102,103 .

Usage Notes
The entirety of the dataset may be downloaded from GitHub (https://github.com/EmoryPcvdLab/EagleVAC) or NITRC 73 . The current version, v449, resides in the EAGLE449 folder of the GitHub repository. As the present authors did not have a role in the acquisition, processing, or distribution of the source atlases, investigators who leverage the atlas are requested to cite these original sources as described in the README file of the repository. It is also requested that investigators consider contributing to iterative refinements of the EAGLE atlas compilation, including, but not limited to, correction of errors, modifications to ROIs, and newly-derived subdivisions of existing vestibular areas documented in published, peer-reviewed research. Finally, investigators should be aware of the number of simultaneous tests (number of ROIs) relative to their sample size when leveraging these parcellations.

code availability
The BASH shell script used for merging of source atlases has also been made available on the GitHub repository as merge_code.bash. Investigators who wish to replicate the workflow will need to download the original source atlases and adjust file paths in the shell script to point to them. The script requires a recent version of the AFNI suite 70 .